Maria Katharaki

Assessing the efficiency and managing the performance of Greek tax offices

Purpose – The aim of this paper is to study the technical and scale efficiency of a set of tax offices (Inland Revenue) in Greece during the period 2001‐2006.Design/methodology/approach – The methodology used to estimate efficiency scores and Greek tax office ranking was the data envelopment analysis. In addition window analysis was used to detect efficiency trends and stability over time. Tobit analysis was applied to explain whether non‐discretionary factors play a role in tax offices performance.Findings – The results underline that “scale size” and the structure of regional economy where tax offices operate are important factors affecting their efficiency.Research limitations/implications – Despite the limitations related to the data set, the empirical work suggests that future research may need to concentrate on the dynamic factors i.e. characteristics of the regional where the tax office is situated which could play a significant role in a tax office performance.Practical implications – The analysi...

An empirical study of comparing DEA and SFA methods to measure hospital units’ efficiency

The paper aims to examine the data envelopment analysis (DEA) and stochastic frontier analysis (SFA) results in order to facilitate a common understanding about the adequacy of these methods, defining any differences in healthcare efficiency estimation. A two-stage bootstrap DEA method and the Translog formula of the SFA were performed. Multi-inputs and multi-outputs were used in both of the approaches assuming two scenarios either including environmental variables or not. Thirty-two Greek public hospital units constitute the sample. DEA and SFA were found to yield divergent efficiency estimates due to many factors such as the nature of the environmental variables, the measurement error and other random factors. Environmental variables being hospital status and geographical position were found significantly correlating with inefficiency. The analysis concludes that the choice of the appropriate mathematical form depends on the expertise of the researcher and the purpose of the evaluation.

SFA vs. DEA for measuring healthcare efficiency: A systematic review

Abstract: Frontier techniques have been used to measure healthcare provider efficiency in hundreds of published studies. Although these methods have the potential to be useful to decision makers, their utility is limited by both methodological questions concerning their application. The aim of this paper is to search articles applying combined data envelopment analysis (DEA) and stochastic frontier analysis (SFA) in order to facilitate a common understanding about the adequacy of these methods, defining any differences in healthcare efficiency estimation and the reasons that are behind this. A systematic review of 21 such studies published the last decade was conducted. Only studies written in English were considered. Results are summarized in a form of meta-analysis in order to synthesize results and draw out further implications. Overall, DEA and SFA were found to yield divergent efficiency estimates due to many factors such as statistical noise, how inputs and outputs were defined, as well as data availability. Researchers, besides the combination of models to measure efficiency, lately have introduced environmental variables in their analyses, aiming at better understanding the relationship of these factors to efficiency and thus achieving a better decision making process. In any case the analysis concludes that there is a need for careful attention by stakeholders since the nature of the data and its availability influence the measurement of efficiency and thus it is necessary to model the behavior which generates the data by choosing the appropriate mathematical form.